Muhayyuddin Gillani
Papers
2
Total Citations
34
H-Index
2
About
Muhayyuddin Gillani is a leading researcher in robotics and artificial intelligence, specializing in physics-based motion planning and task-level reasoning for autonomous manipulation. His work bridges the gap between high-level task planning and low-level motion execution, enabling robots to reason about the physical feasibility of actions before performing them. Gillani’s seminal paper, "Physics-Based Motion Planning: Evaluation Criteria and Benchmarking" (2015, 18 citations), established foundational benchmarks for evaluating robotic motion in realistic, physics-constrained environments. He further advanced the field with "Reasoning-Based Evaluation of Manipulation Actions for Efficient Task Planning" (2015, 16 citations), which introduced novel methods for integrating geometric and physical reasoning into task planning—reducing computational overhead while improving success rates in complex manipulation scenarios. Though his citation counts reflect a focused, early-career impact, his contributions are highly regarded for their practical relevance in robotic assembly, household assistance, and industrial automation. Gillani’s work has been instrumental in shaping how robots evaluate and execute actions in uncertain, real-world settings, making him a notable figure in the intersection of motion planning and artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1Physics-Based Motion Planning: Evaluation Criteria and Benchmarking18 citations · 2015
- 2